Method for de-interleaving received radar pulses using dynamically updated weights

ABSTRACT

The present invention provides a method for separating, or de-interleaving, a stream of radar pulses, interleaved in time, received by a receiving antenna ( 10 ) and receiver ( 12 ) from several radar sources. De-interleaving the stream of received pulses may include forming clusters of pulses having similar parameter values around anchor points, where each cluster is defined by a window around its anchor point. The dimensions of each window may be determined by a weighted distance, i.e., a measure of dissimilarity, calculated using weights. Each weight may depend inversely on the measurement error in the parameter with which the weight is associated. Each anchor point may have a set of weights adjusted to its parameter values, and which may change as operating conditions change. The weights may be determined using a method including a calibration step, which may include injecting pulses with known parameters into the receiver ( 12 ).

BACKGROUND

1. Field

One or more aspects of embodiments according to the present inventionrelate to analyzing received radar pulses and in particular tode-interleaving interleaved radar pulses received from multiple sources.

2. Description of Related Art

When a military asset such as an aircraft is simultaneously illuminatedby multiple radar systems, it may be useful to sort the received radarpulses into groups, or clusters, according to their source. An assetmay, for example, be illuminated by several different radars fromdifferent directions, each having a different combination of amplitude,carrier frequency, pulse width, and modulation type. The received radarpulses may be detected and analyzed by a radar analysis system such as aradar warning receiver (RWR), which may then identify each source asbeing, for example, ship-board radar, aircraft radar, or missile radar.

Radar pulses from multiple sources may be interleaved in time when theyarrive at the radar analysis system. As a first step in analyzing thereceived pulses it may be desirable to de-interleave them, i.e., to formmultiple individual pulse trains, each corresponding to one of the radarsources. This may be particularly important for determining certaincharacteristics of each source: in a stream of pulses from severalsources, for example, each operating at a different pulse repetitionrate (PRR), it is difficult to infer the PRR of any one source withoutfirst separating, i.e., de-interleaving, the stream into separate pulsetrains, one pulse train for each source. Once the stream isde-interleaved the PRR of each source is, in the ideal case, simply therate at which pulses occur in the corresponding pulse train. Even ifsome pulses are lost in processing, the PRR of a given source may beestimated from the remaining pulses, for example by inserting pulses asneeded to produce a regular sequence of pulses. Other attributes such asthe carrier frequency may be determined from a single pulse, but it maybe possible to determine it more accurately from a series of pulsesoriginating from the same source.

Prior art systems may perform de-interleaving by grouping receivedpulses into “clusters” of similar pulses. Pulses that are, according tosome measure of similarity, sufficiently similar, are deemed to haveoriginated from a single source, and pulses that are dissimilar aredeemed to have originated from different sources. Various attributes, orparameters, may be compared when assessing the degree of dissimilarity,or “distance,” between pulses, including frequency, the direction fromwhich the pulses arrived or angle of arrival (AOA), pulse width, andamplitude. A weighted measure of distance may be used. In such a measurea weight may be defined for each parameter and differences in anyparameter multiplied by the corresponding weight.

Selecting the weights for a weighted distance generally involves makinga compromise between the respective likelihoods of two types of error.If a weight is made too large, pulses originating from the same sourcemay be incorrectly classified as originating from different sources; ifthe weight is made too small, pulses originating from different sourcesmay incorrectly be classified as originating from the same source. Ifthe measurement error in a parameter is large, it may be preferable touse a small weight, so that variations in the measured value due tomeasurement error do not cause pulses, which in fact are quite similar,to be classified as originating from different sources. Thus the optimumweights may vary, depending on operating conditions. At hightemperature, for example, amplifier noise in the receiver may cause themeasurement error for some parameters to increase, with the result thatsmaller weights may be preferred at higher temperatures.

In prior art de-interleavers, the weights may be fixed prior tooperation, and they may be independent of the pulse parameters. Weightschosen for low temperature operation may then be too large at hightemperatures, and, conversely, weights chosen for high temperatures maybe too small for good performance at low temperatures. Similarly theoptimum weights may also depend on the parameter values. The measurementerror in pulse width may be greater, for example, for short pulses thanfor long pulses, so that weights chosen for small pulse width may be toosmall when used for long pulses, and weights chosen for long pulses maybe too large when used for short pulses. Thus there is a need for ade-interleaving system capable of performing well over a range ofoperating conditions and pulse parameters.

SUMMARY

Embodiments of the present invention provide a method for separating, orde-interleaving, a stream of radar pulses received by a radar analysissystem from several radar sources, and interleaved in time.De-interleaving the stream of received pulses may include formingclusters of pulses having similar parameter values around anchor points,where each cluster is defined by a window around its anchor point. Thedimensions of each window may be determined by a weighted distance,i.e., a measure of dissimilarity calculated using weights. Each weightmay depend inversely on the measurement error in the parameter withwhich the weight is associated. Each anchor point may have a set ofweights adjusted to its parameter values, and which may change asoperating conditions change. The weights may be determined using amethod including a calibration step, which may include injecting pulseswith known parameters into the receiver, to determine the variation inthe measured values of the corresponding pulse parameters.

According to an embodiment of the present invention there is provided amethod of determining whether a received pulse, in a stream of pulsesreceived by a radar receiver, is a member of a cluster, the clusterhaving an anchor point, the received pulse and the anchor point eachhaving a respective feature vector, each feature vector having amultiplicity of features, the method comprising: generating at least oneweight corresponding to a feature, calculating, using the weight, aweighted distance between the feature vector of the received pulse andthe feature vector of the anchor point, comparing the weighted distanceto a threshold, and determining that the received pulse is a member ofthe cluster if the weighted distance is less than the threshold, whereinthe generating at least one weight corresponding to a feature comprises:injecting pulses of known characteristics into the radar receiver duringoperation, determining the variation in the feature measured, andcalculating the weight as a function of the variation in the featuremeasured.

In one embodiment, the feature is selected from the group consisting of:pulse width, pulse carrier frequency, elevation angle of arrival,azimuth angle of arrival, and pulse amplitude.

In one embodiment, the generating at least one weight corresponding to afeature is repeated after the elapse of a predetermined length of time.

In one embodiment, the generating at least one weight corresponding to afeature is repeated after a change in an environmental conditionexceeding a predetermined amount.

In one embodiment, the weighted distance is the weighted l₂ distance.

In one embodiment, weighted distance is the weighted l₂ distance whereinthe matrix of weights is the inverse covariance matrix.

According to an embodiment of the present invention there is provided amethod of determining whether a received pulse, in a stream of pulsesreceived by a radar receiver, is a member of a cluster, the clusterhaving an anchor point, the received pulse and the anchor point eachhaving a respective feature vector, each feature vector having amultiplicity of features, the method comprising: generating at least twoweights corresponding to a feature, calculating, using the weights, aweighted distance between the feature vector of the received pulse andthe feature vector of the anchor point, comparing the weighted distanceto a threshold, and determining that the received pulse is a member ofthe cluster if the weighted distance is less than the threshold, whereinthe calculating the weighted distance comprises selecting a weight fromthe at least two weights based on the corresponding feature in thefeature vector of the anchor point.

In one embodiment, the at least two features are selected from the groupconsisting of: pulse width, pulse carrier frequency, elevation angle ofarrival, azimuth angle of arrival, and pulse amplitude.

In one embodiment, the generating at least two weights corresponding toa feature is repeated after the elapse of a predetermined length oftime.

In one embodiment, the generating at least two weights corresponding toa feature is repeated after a change in an environmental conditionexceeding a predetermined amount.

In one embodiment, the weighted distance is a weighted l₂ distance.

In one embodiment, the weighted l₂ distance is the Mahalanobis distance.

According to an embodiment of the present invention there is provided asystem for de-interleaving pulses in a series of received pulses,comprising: a receiver for generating a pulse parameter vector for eachreceived pulse, a pulse generator for generating a set of calibrationpulses, and a de-interleaver configured to classify, using a set ofweights, each received pulse into one of a multiplicity ofde-interleaved pulse trains, wherein the de-interleaver comprises aweighting controller for generating the set of weights, the weightingcontroller being configured to determine the set of weights duringoperation from pulse parameter vectors corresponding to the set ofcalibration pulses.

In one embodiment, the weighting controller is further configured toreceive data on the operating environment of the system, and to adjustthe weights based on the received data.

In one embodiment, each weight in the set of weights corresponds to anelement of the pulse parameter vectors.

In one embodiment, the pulse parameter vectors comprise a parameterselected from the group consisting of: pulse width, pulse carrierfrequency, elevation angle of arrival, azimuth angle of arrival, andpulse amplitude.

In one embodiment, the de-interleaver is further configured to triggerthe weighting controller to determine the set of weights upon the elapseof a predetermined length of time after the previous trigger.

In one embodiment, the de-interleaver is further configured to triggerthe weighting controller to determine the set of weights upon apredetermined change in environmental conditions.

In one embodiment, the de-interleaver is configured to classify, using aset of weights in a weighted l₂ distance, each received pulse into oneof a multiplicity of de-interleaved pulse trains.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, aspects, and embodiments are described in conjunction with theattached drawings, in which:

FIG. 1 is a block diagram of a system including a de-interleaveraccording to an embodiment of the present invention,

FIG. 2A is an exemplary plot of pulse width measurement variance used togenerate weights according to an embodiment of the present invention,

FIG. 2B is an exemplary plot of carrier frequency measurement varianceused to generate weights according to an embodiment of the presentinvention,

FIG. 2C is an exemplary plot of angle of arrival measurement varianceused to generate weights according to an embodiment of the presentinvention,

FIG. 3 is a plot of cluster windows and clusters in a two-dimensionalfeature space according to an embodiment of the present invention, and

FIG. 4 is a flow chart illustrating a method of de-interleavingaccording to an embodiment of the present invention.

DETAILED DESCRIPTION

The detailed description set forth below in connection with the appendeddrawings is intended as a description of the presently preferredembodiments of a method for de-interleaving received radar pulses, usingdynamically updated weights, provided in accordance with the presentinvention and is not intended to represent the only forms in which thepresent invention may be constructed or utilized. The description setsforth the features of the present invention in connection with theillustrated embodiments. It is to be understood, however, that the sameor equivalent functions and structures may be accomplished by differentembodiments that are also intended to be encompassed within the spiritand scope of the invention. As denoted elsewhere herein, like elementnumbers are intended to indicate like elements or features. The term“processing unit” is used herein to include any combination of hardware,firmware, and software, employed to process data or digital signals.Processing unit hardware may include, for example, application specificintegrated circuits (ASICs), general purpose or special purpose centralprocessing units (CPUs), digital signal processors (DSPs), graphicsprocessing units (GPUs), and programmable logic devices such as fieldprogrammable gate arrays (FPGAs).

Referring to FIG. 1, in an embodiment of the present invention, areceiving antenna 10 connected to a receiver 12 receives incoming radarpulses. The receiver 12 then characterizes each received pulse in termsof various parameters, including for example amplitude, time of arrival,pulse width, angle of arrival in azimuth and elevation, intentionalmodulation on the pulse, and carrier frequency, and delivers a stream ofpulse parameter vectors to a de-interleaver 16. The de-interleaverclassifies the pulses into clusters and outputs the contents of eachcluster as a separate pulse train 18. During the classification process,each received pulse may be classified as part of a cluster, or not,depending on whether it is sufficiently close to the center of thecluster. This determination may be made by a measure of distance usingweights. The weights may depend on the parameter values, and on externalenvironmental conditions such as temperature, and they may periodicallybe revised, either after the elapse of a predetermined time interval orwhen an external environmental condition changes by a predeterminedamount. A process known as calibration, or built-in test, may be used togenerate revised weights. In such a process, pulses with well knownparameters may, under the control of the de-interleaver 16, be injectedby a pulse generator 22 into the receiver 12, and the resultingcalibration pulse parameter vectors may be fed into a weightingcontroller 20, which then may establish revised weights based on thevariation in the measured parameters for series of nominally identicalcalibration pulses. In one embodiment, the de-interleaver may be aprocessing unit.

The pulse parameters measured by the receiver may differ at leastslightly from the true parameters of the emitted radar pulses, for anumber of reasons, including atmospheric effects, the Doppler effect,and noise and distortion in the receiver. For example, the nominal pulsewidth of pulses emitted by a particular radar may be 1 microsecond (μs),and the receiver may measure the pulse width of a particular pulse asbeing 0.8 μs or 0.9 μs. Even identical pulses emitted from a singleradar source may therefore result in different pulse parameter vectors.Part of the task of the de-interleaver, therefore, is to determinewhether pulses that differ somewhat nonetheless originated from the sameradar source.

Not all parameters may be useful for the purpose of classifying thepulses into clusters. A parameter may vary so little between differenttransmitting radar systems that its variation cannot be measured in ameaningful way, and its use may therefore not facilitate theclassification of the received pulses. The de-interleaver may thereforeselect a subset of the received parameters to be used in classifying thereceived pulses into clusters. The parameters in this subset are knownas “features,” and they form a feature vector for each pulse to beclassified. Each n-dimensional feature vector corresponds to a point inthe n-dimensional feature space, and the terms “point,” “featurevector,” and “pulse” are used interchangeably herein to denote a givenpulse's features.

Pulses may be classified into clusters using an algorithm relying on“anchor points.” The first pulse received, and any subsequently receivedpulse which is not sufficiently similar to previously received pulses,becomes an “anchor point” which defines a new cluster centered on thatanchor point. Whether a subsequently received pulse belongs in anestablished cluster may be determined by the degree of dissimilarity, ordistance, between the subsequently received pulse and the anchor pointfor the cluster. If the distance between the pulse and the anchor pointis less than a predetermined threshold distance, then the pulse isclassified as belonging to the cluster, if the distance exceeds thethreshold then the pulse becomes a new anchor point. Equivalently, anypulse falling within a “window” around the anchor point is classified asbelonging to the cluster. This window is the region of feature spacewithin which all points are nearer the anchor point than the thresholddistance. For the classification technique to be unambiguous, thewindows must not overlap. If a pulse falls outside a cluster window butsufficiently close to the window that making the pulse into an anchorpoint would result in overlapping windows, then it may be necessary todiscard the point, or reduce the size of one or both windows to avoidoverlap.

The distance d between a pulse to be classified and an anchor point maybe calculated, for example, as the Euclidean distance, given by

${d\left( {x,y} \right)} = \sqrt{\sum\limits_{i = 1}^{N}\left( {x_{i} - y_{i}} \right)^{2}}$

where x is the anchor point feature vector and y is the feature vectorof the pulse to be classified, and x_(i) and y_(i) are the i^(th)features (i.e., the i^(th) elements of the feature vectors) of theanchor point and of the pulse to be classified, respectively.

It may be preferable to use a weighted distance. As used herein, a“weighted distance” is any measure of dissimilarity using weights. Anexample of a weighted distance is the normalized Euclidean distance,given by

${d\left( {x,y} \right)} = \sqrt{\sum\limits_{i = 1}^{N}\frac{\left( {x_{i} - y_{i}} \right)^{2}}{\sigma_{i}^{2}}}$

where σ_(i) ² is the variance of the i^(th) feature. Another example isthe more general weighted l₂ distance, given by

d(x, y)=√{square root over ((x−y)^(T) B(x−y))}{square root over((x−y)^(T) B(x−y))}

where B is a matrix of weights, and x is again the anchor point featurevector and y the feature vector of the pulse to be classified. If thematrix of weights B is the inverse covariance matrix, then this distanceis the Mahalanobis distance. Each anchor point may have a set of weightsassociated with it, to be used for calculating the distance between theanchor point and any pulse.

Referring to FIGS. 2A-2C, the measurement error for a feature may dependon the value of the feature itself For example, as illustrated in FIG.2A, which illustrates the fractional error β in the measurement of thepulse width as a function of the pulse width, the fractional error maybe significantly larger for pulses shorter than 40 nanoseconds (ns) thanfor longer pulses. The curve 40 representing the functional relationshipbetween the fractional pulse width measurement error and pulse width maybe used to generate a weight for any given anchor point pulse width. Theweight may for example be chosen to be inversely proportional to themeasurement error. Similarly, FIG. 2B and FIG. 2C show exemplaryvariations of fractional frequency measurement error φ and fractionalangle of arrival error δ as a function of frequency, respectively. Here,angle of arrival may refer, for example, to the azimuth component of theangle of arrival or to the elevation component. The curves 40, 42, and44 in FIGS. 2A-2C do not represent experimental data, they arehypothetical curves shown for the purpose of illustrating the principlesof operation of the present invention. The measurement error may dependalso on environmental parameters such as the temperature of the receiverbecause, for example, noise or distortion in amplifiers in the receivermay depend on temperature.

It may be preferable to use a large weight for a feature which thereceiver is able to measure with high accuracy, as even small variationsin the measured value of such a feature may indicate that thecorresponding pulses originated from different radar sources. Converselyit may be preferable to use a small weight for a feature the measuredvalue of which, as a result of receiver measurement error, variesgreatly even for identical received pulses, because in this case evensignificant differences in this feature may not indicate that the pulsesoriginated from different radar sources. Weights inversely proportionalto the variances in the measured features for identical pulses, orrelated in some other way to the inverse variance or covariance, maytherefore be used.

If a weighted distance, such as the weighted l₂ distance, is used, thenthe weights may be selected in a manner depending on external conditionssuch as temperature, or on the features of the anchor point, i.e., thelocation of the anchor point in feature space. Allowing the weights todepend on the features of the anchor point, and on the externalenvironment, may result in a significant performance improvement overprior art embodiments in which a single “set and forget” vector ofweights, selected prior to operation and unchanged for all anchor pointsis used. In a system with the fractional frequency measurement errorillustrated in FIG. 2B, for example, a small weight may be appropriatefor low and high frequencies, and a larger weight for intermediatefrequencies. In a prior art embodiment with a single fixed weight, theweight may be too small at intermediate frequencies, or too large at lowand high frequencies, or both. Moreover, by remaining fixed duringoperation, the weight in such a prior art embodiment may be too large ortoo small at high or low temperatures, for example, even if it isoptimum for some particular temperature and frequency.

The weights may be determined by various methods. Empirical data on thevariation in measured parameters may be obtained from range tests, inwhich the receiver is illuminated by several known radar sourcessimultaneously. Numerical models of the mechanisms causing measurementerrors may also be used to estimate the expected variation in measuredparameters for identical pulses. During operation, a calibration processmay be used to generate revised weights. In this process, calibrationpulses having well known pulse parameters may be injected into thereceiver. They may then be processed by the receiver in the same manneras pulses received from the receiving antenna, and a pulse parametervector corresponding to each calibration pulse may be sent to thede-interleaver by the receiver. The de-interleaver may then send thepulse parameter vectors on to the weighting controller, which maygenerate revised weights based on the true characteristics of thecalibration pulses and on the received pulse parameter vectors. If thedependence is known, information about external environmental conditionsmay also be incorporated into the calculation of the weights. Forexample, if an increase in temperature results in a known increase inthe pulse width measurement error, then the pulse width weight may bereduced accordingly when the temperature increases. A similar result maybe realized if a new calibration is performed when the temperaturechanges. An increase in temperature may trigger a new calibration, whichwill reveal that the pulse width measurement error is higher, and, inthis case too, the corresponding weight will be reduced accordingly.

Referring to FIG. 3, cluster windows may be illustrated as ellipses orcircles in a two-feature example. In the scatter plot shown, eachsymbol, viz. asterisk (“*”), “O” symbol, or pound symbol (“#”),represents the feature vector, or point in the feature space,corresponding to a received pulse. Each feature vector in this examplecontains two features, the pulse width and the frequency. The poundanchor point 66, i.e., the anchor point for the cluster of pulsesidentified by pound symbols, is the center of the window for thatcluster, which contains all pulses falling within the window 68, acircle around the pound anchor point 66. The circular shape of thiswindow may result, for example, from using an l₂ distance with B₁₁=B₂₂and B₁₂=B₂₁=0, where the subscript 1 may refer to the first feature,i.e., pulse width, and the subscript 2 may refer to the second feature,i.e., frequency. Similarly the circular window 62 for the “O” cluster iscentered on the anchor point 60 labeled “O” so that other points 64falling within this window 62 are classified as being part of thiscluster and as originating from the same source as the anchor point 60.

If the measurement error and resulting scatter are larger at lower pulsewidth, then in this example using the same window size may result inincorrect classification of some points. For example, if the anchorpoint 80 is first established as an anchor point with the relativelysmall window 85, then some points, such as the points 84 which fallclose to it, may be classified as being part of the cluster, but anotherpoint, such as the point 86, which may originate from the same source,may fall sufficiently far from the anchor point 80 to be classified as anew anchor point, with its own window 88. Subsequently received pointssuch as the points 90 which fall within the window 88 will then beincluded in the cluster defined by the anchor point 86, and thealgorithm may deem the pulses 90 as well as the anchor point 86 to haveoriginated from a radar source separate and distinct from that whichproduced the anchor point 80 and the points 84 in its cluster. This maybe incorrect; all the points may correspond to the same source but mayhave been distributed more widely in the two-dimensional feature spacebecause of larger measurement error at low pulse widths.

If, on the other hand, the window is made larger, i.e., the weights madesmaller, to correspond to the larger measurement error at low pulsewidths, and a window such as the window 82 is used instead, then thepoint 86, and, indeed, all of the other points shown as asterisks, mayfall inside the window and be classified as part of the same cluster.

A calibration process which determines the measurement error in eachfeature at various points in feature space may be used to generateweights which take this variation into account. For example, the pulsegenerator may generate a series of nominally identical calibrationpulses with low pulse widths, and the weighting controller may use theobserved variance in the corresponding pulse parameter vectors receivedfrom the receiver to set the weights for low pulse width anchor points.The pulse generator may also generate a series of nominally identicalcalibration pulses at higher pulse widths. Again, the weightingcontroller may use the observed variance in the corresponding pulseparameter vectors received from the receiver to set the weights forhigher pulse width anchor points. The observed variance may be smallerfor the higher pulse width calibration pulses than for the lower pulsewidth pulses, and the weighting controller may accordingly set largerweights for higher pulse width pulses, resulting in better performancethan if a single constant weight were used. Series of nominallyidentical calibration pulses may similarly be used at other points infeature space to set the corresponding weights.

The calibration process may be effective primarily for determining thevariance due to receiver measurement errors, the variance due toatmospheric effects may, for, example, not be measured by this process.Measurement errors introduced by effects outside of the receiver maynonetheless be estimated using models, based for example on weatherconditions, relative velocities, accelerations, and the like, and thesemeasurement errors may be taken into account by the weighting controllerwhen generating weights.

Referring to FIG. 4, the sequence of steps involved in de-interleaving astream of pulses by classifying them into clusters may be illustratedusing a flow chart. In step 100, initial weights may be determinedempirically at a range, using known radar sources for calibration, orusing numerical models, or by a combination of such methods. Operationbegins in step 102 and a pulse is received in step 104. In step 106, ifthe received pulse is the first pulse, the step 108 of comparing it toexisting cluster windows is skipped, there not being any such windows,and the pulse is classified, in step 112, as the anchor point of a newcluster.

If in step 106 it is determined that the current pulse is not the firstpulse, then the current pulse is compared, in step 108, to all existingcluster windows. Step 108 involves calculating the weighted distancebetween the pulse feature vector and the feature vector of the anchorpoint of each existing cluster, using, in each case, the vector ofweights for that anchor point. If it falls within any such window it isclassified, in step 110, as a member of the corresponding cluster, if itdoes not, it is classified in step 112 as the anchor point for a newcluster. When a new cluster is established in step 112, a window isestablished around it, in step 114. In step 116, several conditions maybe assessed to determine whether a calibration is needed. Theseconditions may include the passage of a certain amount of time since thelast calibration, or a change in the environment, such as a change intemperature, or for example, in the case of a system deployed on anaircraft, a change in altitude. If a calibration is needed, then it isperformed, in step 118, and the resulting revised weights are used insubsequent executions of step 108, until the weights are again revised.Finally operation resumes with the reception of the next pulse, in step104.

Although in the embodiment for which a sequence of steps is illustratedin FIG. 4 de-interleaving ceases while a calibration is performed, thepresent invention is not limited to such a sequence. Calibration andde-interleaving may be performed simultaneously, with the de-interleavercontinuing, during a calibration, to de-interleave pulses that are notcalibration pulses, and routing to the weighting controller only thepulse parameter vectors corresponding to calibration pulses.

Although limited embodiments of a method for de-interleaving receivedradar pulses using dynamically updated weights have been specificallydescribed and illustrated herein, many modifications and variations willbe apparent to those skilled in the art. For example, although thede-interleaving method of the present invention is disclosed in thecontext of a military RWR, it may be equally well be employed in adifferent military radar sensing system such as an electronicintelligence (ELINT) system, or in a civilian system, such as a systemfor tracking civilian aircraft. Accordingly, it is to be understood thatthe method for de-interleaving received radar pulses using dynamicallyupdated weights employed according to principles of this invention maybe embodied other than as specifically described herein. The inventionis also defined in the following claims.

What is claimed is:
 1. A method of determining whether a received pulse,in a stream of pulses received by a radar receiver, is a member of acluster, the cluster having an anchor point, the received pulse and theanchor point each having a respective feature vector, each featurevector having a multiplicity of features, the method comprising:generating at least one weight corresponding to a feature; calculating,using the weight, a weighted distance between the feature vector of thereceived pulse and the feature vector of the anchor point; comparing theweighted distance to a threshold; and determining that the receivedpulse is a member of the cluster if the weighted distance is less thanthe threshold, wherein the generating at least one weight correspondingto a feature comprises: injecting pulses of known characteristics intothe radar receiver during operation; determining the variation in thefeature measured; and calculating the weight as a function of thevariation in the feature measured.
 2. The method of claim 1, wherein thefeature is selected from the group consisting of: pulse width, pulsecarrier frequency, elevation angle of arrival, azimuth angle of arrival,and pulse amplitude.
 3. The method of claim 1, wherein the generating atleast one weight corresponding to a feature is repeated after the elapseof a predetermined length of time.
 4. The method of claim 1, wherein thegenerating at least one weight corresponding to a feature is repeatedafter a change in an environmental condition exceeding a predeterminedamount.
 5. The method of claim 1, wherein the weighted distance is theweighted l₂ distance.
 6. The method of claim 1, wherein the weighteddistance is the weighted l₂ distance wherein the matrix of weights isthe inverse covariance matrix.
 7. A method of determining whether areceived pulse, in a stream of pulses received by a radar receiver, is amember of a cluster, the cluster having an anchor point, the receivedpulse and the anchor point each having a respective feature vector, eachfeature vector having a multiplicity of features, the method comprising:generating at least two weights corresponding to a feature; calculating,using the weights, a weighted distance between the feature vector of thereceived pulse and the feature vector of the anchor point; comparing theweighted distance to a threshold; and determining that the receivedpulse is a member of the cluster if the weighted distance is less thanthe threshold, wherein the calculating the weighted distance comprisesselecting a weight from the at least two weights based on thecorresponding feature in the feature vector of the anchor point.
 8. Themethod of claim 7, wherein the at least two features are selected fromthe group consisting of: pulse width, pulse carrier frequency, elevationangle of arrival, azimuth angle of arrival, and pulse amplitude.
 9. Themethod of claim 7, wherein the generating at least two weightscorresponding to a feature is repeated after the elapse of apredetermined length of time.
 10. The method of claim 7, wherein thegenerating at least two weights corresponding to a feature is repeatedafter a change in an environmental condition exceeding a predeterminedamount.
 11. The method of claim 7, wherein the weighted distance is aweighted l₂ distance.
 12. The method of claim 11, wherein the weightedl₂ distance is the Mahalanobis distance.
 13. A system forde-interleaving pulses in a series of received pulses, comprising: areceiver for generating a pulse parameter vector for each receivedpulse; a pulse generator for generating a set of calibration pulses; anda de-interleaver configured to classify, using a set of weights, eachreceived pulse into one of a multiplicity of de-interleaved pulsetrains; wherein the de-interleaver comprises a weighting controller forgenerating the set of weights, the weighting controller being configuredto determine the set of weights during operation from pulse parametervectors corresponding to the set of calibration pulses.
 14. The systemof claim 13, wherein the weighting controller is further configured toreceive data on the operating environment of the system, and to adjustthe weights based on the received data.
 15. The system of claim 13wherein each weight in the set of weights corresponds to an element ofthe pulse parameter vectors.
 16. The system of claim 13 wherein thepulse parameter vectors comprise a parameter selected from the groupconsisting of: pulse width, pulse carrier frequency, elevation angle ofarrival, azimuth angle of arrival, and pulse amplitude.
 17. The systemof claim 13 wherein the de-interleaver is further configured to triggerthe weighting controller to determine the set of weights upon the elapseof a predetermined length of time after the previous trigger.
 18. Thesystem of claim 13 wherein the de-interleaver is further configured totrigger the weighting controller to determine the set of weights upon apredetermined change in environmental conditions.
 19. The system ofclaim 13 wherein the de-interleaver is configured to classify, using aset of weights in a weighted l₂ distance, each received pulse into oneof a multiplicity of de-interleaved pulse trains.